73 results about "Torque optimization" patented technology

The invention discloses a robust model prediction control method for mechanical arm trajectory tracking control, and relates to the field of multi-degree-of-freedom mechanical arm trajectory tracking control. According to the method, disturbance and parameter perturbation of a mechanical arm system are converted into lumped disturbance, a mechanical arm system error model is established, and feedback linearization is conducted on an error system based on an inverse dynamics method; based on a mechanical arm system error model, a nominal system model prediction controller is designed, a terminal area, a terminal control law and corresponding terminal cost are designed, and the feasibility of rolling interval optimization in each time step is guaranteed. According to the method, the uncertainty and disturbance of the mechanical arm system can be processed, it is guaranteed that system constraints are met, and high-precision trajectory tracking control and input torque optimization are achieved.

The invention relates to the technical field of electric driving system energy-saving control, and discloses a multi-motor driving system torque optimal distribution method and system, and the method comprises the steps: building a single power unit power loss model of a multi-motor driving system; constructing a fitting straight line segment; constructing a torque-current mapping relation curve; a train speed prediction model, a multi-motor driving system power unit motor rotating speed prediction model, a multi-motor driving system total torque reference value prediction model and a multi-motor driving system power unit power loss prediction model are constructed; establishing a multi-motor driving system energy efficiency evaluation function, a multi-motor driving system stability evaluation function, a multi-motor driving system total torque following evaluation function and a system optimization objective function; designing a learning rate of a control vector; and updating the control vector according to the learning rate, and obtaining an optimized torque distribution coefficient and an optimized torque reference value distributed by each power unit. Therefore, the torque optimization distribution of the multi-motor driving system is realized, and the energy utilization efficiency of the system is improved.

The invention provides a tractor semitrailer full-working-condition active stability control system and method, and belongs to the technical field of vehicle engineering. The system comprises a kinetic model module, a reference quantity determination module and an active stability controller module. The dynamic model module constructs a linear three-degree-of-freedom tractor semitrailer model, a hub motor model and a longitudinal driver model. The reference quantity determination module generates an ideal state value according to the steady state condition of the system and corrects the ideal state value in combination with the road attachment condition. The active stability controller module is divided into three layers, an MIMO-IMFAC controller calculates additional yawing moment, a torque optimization controller optimizes tire load distribution through a quadratic programming algorithm, and a driving / braking torque distribution controller preferentially uses regenerative braking and dynamically adjusts braking torque of the semitrailer according to the yawing moment. By adopting the control system and the control method, the stability and the dynamic response capability of the vehicle under complex working conditions are remarkably improved.

The invention discloses an intelligent control method and system for a motor driver, and the method comprises the steps: building an acoustoelectric incidence matrix through collecting harmonic current and sound pressure fluctuation data in the operation process of a motor, and forming a fault feature library; identifying an available fault mode to determine an energy collection point, and performing phase deviation processing on the collection point to generate an auxiliary driving signal; performing spectrum analysis on the sound pressure fluctuation data to obtain an acoustic characteristic spectrum, extracting an efficiency indication tone through characteristic decomposition, mapping the efficiency indication tone into a torque optimization parameter, and establishing a noise reduction control table; performing spectrum analysis on the enhanced control domain to identify a high-energy frequency band, executing a frequency shift operation to generate a safety frequency band signal, and forming a multi-frequency band management strategy in combination with a noise reduction control table; a management strategy is decomposed into parallel control flows for sequential staggered arrangement, and an energy-saving control matrix is generated; and generating a PWM control signal based on the matrix, carrying out edge reconstruction, and obtaining a softened edge waveform through an anti-resonance injection technology to complete intelligent control of the motor driver.

The invention relates to the technical field of vehicle control, in particular to a vehicle trajectory tracking and driving stability fault-tolerant control method and device, and can solve the challenges that lumped disturbance prior upper bound unknown, communication network congestion and actuator faults are difficult to cope with at the same time in the prior art to a certain extent. And the buffeting problem caused by the traditional sliding mode switching gain and the singularity problem in the solving process are solved. The method comprises the following steps: establishing a vehicle dynamics model, a control error model and a related model; designing an adaptive robust terminal sliding mode trajectory tracking controller and a stability controller; event triggering conditions are designed, and the influence of communication network congestion is reduced; and a torque optimization distribution strategy with an actuator fault factor is designed, so that the fault-tolerant capability of the system is improved. The problems of system parameter uncertainty, external disturbance, communication resource limitation, buffeting, singularity, actuator faults and the like can be effectively solved, and therefore accurate control over the intelligent vehicle is achieved under the complex driving working condition.

The invention discloses an outer rotor permanent magnet synchronous motor torque optimization method, which comprises the following steps: 1) design parameter selection: selecting key characteristics of a motor stator slot as design parameters, including slot shoulder height Hs1, tooth length Hs2, chord length Bs0 and slot shoulder width Bs1; 2) finite element model construction: establishing a multi-target finite element model with cogging torque, torque pulsation and average torque as targets; 3) establishing an analytic model: establishing the analytic model of the motor torque by using an energy method and a repetitive unit method, and comparing the analytic model with the finite element model to verify the accuracy of the analytic model; 4) response surface model construction: based on the simulation data of the finite element model, performing finite element analysis by adopting a central composite design CCD, constructing a response surface model, performing sensitivity analysis on design variables, and determining the influence of each variable on an optimization target; and 5) optimization efficiency improvement: determining optimal configuration in a design space by using an adaptive genetic aggregation algorithm AGA, and achieving a multi-objective optimization effect.

The invention discloses an intelligent automobile transverse control method based on sensor measurement reconstruction under network attacks, and relates to automobile intelligent safety and automatic driving. A model prediction control MPC controller based on sensor measurement reconstruction is constructed, and accurate control over transverse movement of the vehicle is achieved. The system monitors sensor data in real time, detects sensor data abnormity caused by network attack, starts a measurement reconstruction mechanism, and corrects the data by using a redundant sensor or an algorithm model. A lower-layer torque optimal distribution controller is designed, the controller intelligently adjusts output torques of four hub motors according to expected yaw moment output by an upper-layer MPC and vehicle state information, so that accurate control over the yaw moment of the vehicle is achieved, transverse tracking errors are reduced, and the driving stability and the dynamic performance of the vehicle are improved. A transverse cooperative control rule is provided, and comprehensive optimization of transverse control of the vehicle is achieved by coordinating work of an upper-layer MPC controller and work of a lower-layer torque optimization distribution controller.

The invention provides a torque optimization type flat axial magnetic flux motor which comprises a main body assembly, and the main body assembly comprises two stator iron cores, an electromagnetic ring, a mounting frame, an electromagnetic coil, a rotor disc, a mounting seat, two limiting blocks, two fixing plates, two upper magnetic blocks, two limiting grooves, two limiting rods, a supporting spring and a through groove. And the through grooves are symmetrically formed in the rotor disc. When the robot needs to bear a large load, the electromagnetic ring pushes the sliding block through the lower magnetic block, the sliding block drives the clamping blocks, the two clamping blocks get close to each other, then the electromagnetic ring works, the upper magnetic block is pushed through magnetic force to move in the direction away from the mounting frame, meanwhile, the mounting base drives the magnetic steel, and due to the fact that the mounting base generates displacement, the magnetic steel is driven to rotate. And the torque of the axial magnetic flux motor is in direct proportion to the cube of the radius of the rotor, so that the torque can be remarkably improved by increasing the radius of the rotor, the motor is further suitable for a scene with a relatively large load, and the motion performance of the robot is ensured.

The invention belongs to the field of vehicle control, and particularly relates to an additional yawing moment distribution control strategy for a hybrid commercial vehicle in a combined driving mode, which comprises the following steps of: judging the steering state of the vehicle in the combined driving mode; for insufficient and excessive steering states, determining an optimal distribution target of the additional yaw moment, namely target braking wheels; the method comprises the following steps: selecting a control quantity, establishing an optimization objective function according to a friction ellipse theory and a ratio of a wheel longitudinal force to an adhesion force, determining constraint conditions according to a lateral stability control demand, a road adhesion condition and a driving system limitation, and solving an optimal control problem under multiple constraint conditions by adopting a quadratic programming algorithm. According to the method, the additional yawing moment value serves as a control target, torque optimization distribution among the wheels is carried out in the engine and motor dual-drive mode, the target wheels are braked, the motor output torque is adjusted, the longitudinal force of the wheels is changed, the additional yawing moment is applied, and the maneuverability and lateral stability of the vehicle under the complex working condition are improved.

The invention relates to the technical field of rail transit trains, and provides a motor torque distribution method, device and equipment for independent rotating wheels of a train, and the method comprises the steps: obtaining a state-space equation taking an independent wheel set and carriage movement as a research object; determining constraint conditions of the torque optimization function based on the state-space equation; determining a torque optimization function according to the train parameters and the wheel parameters; determining a torque distribution instruction of each wheel motor by taking minimization of a torque optimization function as a target based on a constraint condition; and controlling the motor torque output of each independent rotating wheel according to the torque distribution instruction. According to the method, the problem that guiding control and creep control are difficult to cooperate is solved, and the train operation stability and the wheel rail adhesion utilization rate are improved.

The invention discloses an agricultural machine, a steering control method and device thereof and a medium, and belongs to the technical field of agricultural machines. The method comprises the following steps: estimating an ideal yaw velocity and an ideal side slip angle of the agricultural machine; the actual yaw velocity and the actual side slip angle of the agricultural machine are obtained; based on a first difference value between the ideal yaw velocity and the actual yaw velocity and a second difference value between the ideal side slip angle and the actual side slip angle, executing a feedback control algorithm to determine a compensation yaw moment of the agricultural machine; and based on the compensation yawing moment, adapting to the current steering working condition and carrying out rear wheel torque optimal distribution for the agricultural machinery. Smooth and stable walking and steering can be achieved, and the problem that the agricultural machine slips due to unreasonable drive torque distribution under the working condition that the adhesive force is very low is solved.

An integrated control method for handling stability of a distributed drive electric vehicle, and a related device, which belong to the technical field of vehicle handling stability control. According to the method, piecewise linear fitting is performed on a magic formula tire model to establish a piecewise affine tire model, a hybrid logic dynamic model is established on the basis of the piecewise affine tire model, an upper hybrid model prediction controller and a lower four-wheel torque optimization distribution controller are established by using a hierarchical integrated control policy, and additional yaw moment, an additional front wheel angle and wheel drive torque are calculated, so that stability control over vehicle handling is achieved. The method can accurately describe change conditions of tire lateral force during vehicle operation, and reduce the calculation amount of a control system to improve the response speed.

The invention discloses a multi-axis distributed driving vehicle torque distribution method based on a conditional solution method. The method comprises the following steps: initializing; designing a torque optimization distribution equation; solving a torque optimization distribution equation; and performing torque control. On the basis of the relation between the longitudinal driving force and the yawing moment of the vehicle and torque distribution, the influence of a tire attachment ellipse, the coupling problem of the longitudinal driving force and the lateral force of the tire and the problem that the vehicle is prone to instability under the nonlinear working condition are considered; a torque optimal distribution equation considering safety constraints such as the road adhesion coefficient and the maximum torque output capacity of the hub motor is designed, and reasonability, reliability and safety of the multi-axis distributed driving vehicle in torque optimal distribution are ensured. According to the method, a solution thought is provided for solving the real-time optimal feasible solution of torque distribution, and the distribution optimality, the solution real-time performance, the torque control precision, the stability and the robustness of the torque optimization distribution of the multi-axis distributed driving vehicle are guaranteed.

The invention discloses a pipeline flange sealing surface bolt fixed-torque fastening method, and relates to the technical field of pipeline fastening, and the method comprises the following steps: S1, collecting the roughness of a bolt hole sealing surface, constructing a scattering matrix, and obtaining a surface fluctuation main directivity index; s2, similar channels are judged according to the roughness Euclidean distance, and connectivity weights between the channels are constructed; s3, mapping the roughness and the surface fluctuation main directivity index into equivalent stiffness to calculate weighted stiffness; s4, calculating a load collaboration degree in combination with a spectrogram structure consistency index and a force distribution dispersion; s5, processing the residual stress time sequence data, and adjusting residual stress distortion in combination with the load collaboration degree and the weighted stiffness; and S6, according to the multi-target evaluation indexes, obtaining an optimal torque value by adopting a hybrid heuristic multi-target optimization algorithm, and applying the optimal torque in stages. By adjusting the pre-tightening force and the torque of the bolt hole, the mechanical behavior of the system is optimized, and the uniformity and the stability of the fastening process are improved by adopting a multi-objective optimization algorithm.

This application discloses an online identification method, apparatus, aircraft, and computer-readable storage medium for aircraft parameters, relating to the field of aircraft technology. The method includes: acquiring first parameters of the aircraft under low-frequency control commands; iteratively calculating an optimization function based on the first parameters to obtain a control efficiency optimization matrix; updating the optimization function based on the control efficiency optimization matrix; acquiring second parameters of the aircraft under variable-frequency control commands; iteratively calculating the updated optimization function based on the second parameters to obtain a gyroscopic torque optimization matrix and a transfer function optimization matrix; and determining a target control efficiency matrix, a target gyroscopic torque matrix, and a target transfer function matrix based on the control efficiency optimization matrix, the gyroscopic torque optimization matrix, and the transfer function optimization matrix. This application enables online identification of aircraft characteristic parameters through optimization functions, improving the convenience of aircraft parameter identification and allowing the aircraft to achieve optimal flight performance under different operating conditions.

The invention discloses a hybrid electric vehicle cooperative energy-saving control method and a hybrid electric vehicle cooperative energy-saving control system, which are used for constructing an integrated control system of vehicle-road cooperative information look-ahead-upper-layer vehicle speed planning-lower-layer ECMS-MPC torque optimization-upper-lower-layer closed-loop cooperative feedback aiming at complex working conditions of urban roads including signal lamp intersections, congested road sections and the like. The core defects of the prior art in the aspects of information dimension, working condition adaptability and control architecture are accurately overcome, and multi-target collaborative optimization of fuel consumption, traffic efficiency, driving comfort and battery life is achieved.

The present invention relates to the field of brushless DC motor torque optimization, and discloses a method for optimizing the torque of an outer rotor brushless DC motor, including establishing a parameterized finite element model of an outer rotor brushless DC motor to solve the performance; constructing a Pearson correlation coefficient matrix framework under the motor model structural parameters and output response; obtaining key structural dimension parameter variables for different response targets; establishing an optimal prediction meta-model that can replace the finite element calculation model; optimizing the meta-model for multiple torque targets to obtain the Pareto optimal frontier; using the CRITIC‑TOPSIS evaluation model to evaluate and sort the relative merits of the Pareto solution set to obtain the optimal structural dimension parameters. Compared with the prior art, the present invention can realize the rapid optimization of the multi-torque performance of the motor, abandon the disadvantage of slow iterative calculation of the finite element model, and the selected evaluation model comprehensively considers the differences and correlations between various torque performance indicators, and its evaluation results are objective and comprehensive.

The invention discloses a screwdriver torque optimization control method based on a neural network. The method comprises the following steps: constructing a contact state diagram of a whole tightening process; node and edge features are extracted by using an isotropic graph neural network, and the clamping force variation is predicted; calculating an energy consistency condition based on a screw tightening physical model and updating edge features; inputting the updated state into the dimension raising dynamic model, and predicting a future state sequence; constructing a model prediction control optimization problem in combination with existing multi-dimensional constraint conditions, and generating an optimal torque instruction sequence; and judging a slip risk based on online gating, and executing a torque reduction and maintenance strategy. According to the method, the physical constraint and the deep learning model are combined, and high precision and high stability of torque control are achieved.

This invention discloses a mechanical leg, a robot, and a torque optimization design method. The mechanical leg includes a first transmission arm, a second transmission arm, and a transmission assembly. The first transmission arm connects to the robot's body and includes a frame with a guide groove extending along its length. The second transmission arm is rotatably connected to the first transmission arm. The transmission assembly includes a knee joint drive motor, a lead screw, a slide block, a connecting rod, and a crank. One end of the lead screw is connected to the output shaft of the knee joint drive motor, and the other end passes through the frame. The slide block is fitted onto the lead screw and has a guide portion that inserts into the guide groove. Rotation of the lead screw drives the slide block to move axially along the lead screw. One end of the connecting rod connects to the slide block, and the other end connects to the second transmission arm via the crank. This mechanical leg, by combining a ball screw mechanism and a crank-slide block mechanism, effectively amplifies the torque of the knee joint drive motor.

This invention discloses a motion control method for a six-wheeled lunar rover based on a hierarchical control structure. The method includes establishing a six-wheeled lunar rover model and a hierarchical control framework comprising a state reference layer, a torque decision layer, and a torque distribution layer. In the state reference layer, a two-degree-of-freedom single-track model is constructed to calculate the ideal yaw rate and center-of-gravity sideslip angle. In the torque decision layer, a double-power-law approach is designed to calculate the longitudinal velocity tracking error, yaw rate tracking error, and center-of-gravity sideslip angle tracking error; a sliding mode control method is used to calculate the generalized longitudinal force, lateral force, and yaw moment. In the torque distribution layer, an objective function is constructed based on the optimal control principle, and the torque distribution for the six wheels is optimized under the constraints of minimizing tire load rate and total motor energy consumption. This invention achieves motion stability control and collaborative optimization through a hierarchical control architecture, a sliding mode variable structure algorithm, and dynamic torque optimization distribution, providing an effective solution for torque control strategies in lunar exploration missions.

A kind of electric vehicle Tip-in anti-collision gear control system and control method, belong to the technical field of automobile driving performance optimization, wherein the electric vehicle Tip-in anti-collision gear control system, including the detection component that detection loosens acceleration pedal and then carries out Tip-in operation and makes the detection component of whole car gear impact risk state, detection component is connected with motor controller by whole car controller to control motor gear front and reducer gear reverse side keeps meshing, the beneficial effects of the present application are, the present application increases reasonable gear torque to motor in the process of vehicle sliding, optimizes the whole car gear impact feeling when Tip-in operation again in the process of low-speed sliding under non-energy recovery state, further improves the driving comfort of whole car.

The invention discloses a wheel-foot robot climbing control method and system based on attitude and torque optimization, and relates to the technical field of robot control. The method comprises the steps that the gravity center of a robot trunk serves as the moment center, and a statics model of a wheel-foot robot on a slope is constructed; quantitatively analyzing the influence of gravity projection, wheelbase and station height of the robot on torque distribution of front and rear wheels, and establishing a torque distribution ratio formula; determining an optimal gravity center projection distance ratio, an optimal axle distance and an optimal station height by taking torque balance as a target; in the actual climbing process of the wheel-foot robot, the projection position of the gravity center of the robot body is obtained in real time, the posture of the wheel-foot robot is adjusted and controlled according to the projection position, the projection position is always located in a safe area of the supporting polygon, and meanwhile the optimal gravity center projection distance ratio, the axle distance and the station height are combined according to the projection position. And torque output of front and rear wheels of the wheel-foot robot is regulated to realize stable climbing. The problem that the wheel-foot robot turns on one side and slips frequently in the process of advancing on the slope can be solved.

The present application relates to the motor technical field, especially a kind of motor tooth slot torque optimization method, device, equipment and storage medium.It is by constructing motor simulation model, and parameter scanning is carried out to motor simulation model, obtains scanning data;Based on scanning data, fitting function is constructed;According to the geometric parameters of motor simulation model, determine parameter boundary condition;According to parameter boundary condition and fitting function, determine target auxiliary slot parameter.The present application is by constructing motor simulation model first, and parameter scanning is carried out to motor simulation model, obtains scanning data, then according to scanning data, fitting function is constructed, reduces the computing power cost, according to the geometric parameters of motor simulation model, determine parameter boundary condition, finally according to fitting function and parameter boundary condition, determine target auxiliary slot parameter, to make the auxiliary slot opened according to the target auxiliary slot parameter can guarantee the output torque of motor and reduce the tooth slot torque of motor.

A torque optimization system for an electrified vehicle having an electrified powertrain including three electric motors a, b, and c and an additional torque generating system includes a set of sensors configured to measure a set of operating parameters of the electrified vehicle and a control system configured to determine a torque relationship between electric motors b and c, solving a three-dimensional (3D) optimization problem for the electrified powertrain, the 3D optimization problem defining torques generatable by one of electric motors b and c, electric motor a, and the additional torque generating system, determine torque commands for the three electric motors a, b, and c and the torque generating system based on the solving of the 3D optimization problem, the determined torque relationship, and the set of operating parameters, and control the electrified powertrain based on the determined torque commands.

The application discloses an intelligent control method and system of a motor driver, which comprises the following steps: collecting harmonic current and sound pressure fluctuation data in the motor operation process, constructing a sound-electricity correlation matrix to form a fault feature library; identifying available fault modes to determine energy collection points, and performing phase offset processing on the collection points to generate auxiliary driving signals; performing frequency spectrum analysis on the sound pressure fluctuation data to obtain acoustic characteristic spectrum, extracting efficiency indicating sound through characteristic decomposition and mapping into torque optimization parameters, and establishing a noise reduction control table; performing frequency spectrum analysis on an enhanced control domain to identify high-energy frequency bands, performing frequency shift operation to generate safe frequency band signals, and combining the noise reduction control table to form a multi-frequency band management strategy; decomposing the management strategy into parallel control flows for time sequence interleaving arrangement to generate an energy-saving control matrix; generating a PWM control signal based on the matrix and performing edge reconstruction, obtaining a softened edge waveform through anti-resonance injection technology, and completing intelligent control of the motor driver.

The present invention relates to the technical field of shield tunnel construction, and specifically discloses an intelligent regulation method for shield tunnels with an ultimate radius in a narrow space, including: obtaining the state information of the shield machine; collecting formation pressure, moisture content, and soil deformation data to obtain formation characteristic information; analyzing and obtaining an optimal construction adjustment strategy based on the formation characteristic information; based on the optimal construction adjustment strategy, using deep reinforcement learning combined with fuzzy PID control to calculate the optimal tunneling trajectory of the shield machine, and obtaining an adaptable construction plan for the ultimate radius in a narrow space; the present invention jointly optimizes the trajectory of the shield machine based on deep reinforcement learning combined with fuzzy PID control, realizes dynamic attitude correction, and reduces the deviation of the tunneling trajectory. The multi-sensor data fusion improves the accuracy of attitude estimation, realizes the reduction of the shield attitude angle error, effectively reduces the number of manual interventions, and improves the construction efficiency; the automatic thrust and torque optimization control avoids attitude mutations caused by formation changes and improves the stability of the shield machine.

This application discloses a method for active thermal management and torque coordinated control of motors in a large eVTOL system, relating to the field of electric vertical takeoff and landing aircraft control technology. The disclosed method for active thermal management and torque coordinated control of motors in a large eVTOL system acquires flight mission data and real-time status data, calculates thermal load assessment data, determines multi-objective optimization weight configuration data, and inputs torque optimization commands to a dynamic optimizer, thereby realizing coordinated control of motor thermal management and torque output. This method can effectively prevent motor thermal imbalance, improve flight control accuracy and system reliability, and avoid failures caused by overheating.

The invention discloses an automobile composite braking torque optimal distribution method based on EMB multi-stage response characteristics. The method comprises the following steps that 1, all sensors collect data signals; step 2, calculating the required braking torque of the whole vehicle and distributing the front and rear braking torque; 3, judging whether the EMB intervenes or not: if the EMB needs to intervene, carrying out a step 4, and if the EMB does not need to intervene, directly carrying out a step 7; 4, primarily distributing a braking torque coefficient based on interval type-2 fuzzy control; step 5, discriminating an EMB working stage; step 6, carrying out secondary distribution on a braking torque coefficient based on EMB multi-stage response characteristics; 7, EMB / regenerative braking is implemented; and 8, whether braking is finished or not is judged. In the re-distribution process of the braking torque coefficient, the working characteristics that the braking torque of the EMB is vacant in the braking torque no-load stage and the braking torque is rapidly changed in the braking torque lifting stage are fully considered, and the braking recovery efficiency and the braking stability of the automobile are effectively improved.

The present invention provides a method and device for controlling the torque distribution of a vehicle, and relates to the field of automotive technology. In this application, the current state of the vehicle (braking or accelerating) is accurately identified based on the vehicle state information, such as vehicle speed, acceleration, battery parameters and other multivariate data, so that the control center can enter the corresponding control mode, which speeds up the response rate of the vehicle driving controller to accelerate or brake, so as to coordinate and control the torque distribution between motors and improve the overall working efficiency of the motors. Then, the inter-axle torque is optimized and distributed according to the vehicle state information and road condition information. The system performance is improved based on the trial-and-error interaction with the environment through reinforcement learning, based on the observation value and the analysis of the system behavior. The optimal control strategy is usually obtained with the goal of maximizing the cumulative reward function. It can not only improve the vehicle's handling stability and safety, but also has great potential in improving economy and the energy utilization rate of the vehicle.

The present invention provides a regenerative braking method and electromechanical system applicable to all operating conditions. The brake control unit receives brake pedal opening, vehicle speed, and wheel speed signals, calculates braking intensity using a fuzzy controller, obtains motor torque and hydraulic torque using a braking torque optimization distribution module, and determines whether a downshift is necessary using a downshift strategy module. The motor controller receives control instructions from the brake control unit and controls the motor to output the corresponding torque. The hydraulic controller receives control instructions from the brake control unit and controls the hydraulic brake system to output the corresponding hydraulic torque. The DHT controller receives control instructions from the brake control unit and controls the clutch and synchronizer to implement mode / gear switching. The downshift strategy module includes a downshift switching function consisting of the inverse of the objective function increment and a periodic penalty switching index to determine the downshift switching conditions. This invention effectively prevents frequent mode / gear switching and upshifting.